基于支持向量机的个人信用评估模型研究  

The Model of Personal Credit Risk Assessment On Support Vector Machine

作　　者：吴冲[1] 王萤[1] 郭英见[1] 

机构地区：[1]哈尔滨工业大学管理学院,黑龙江哈尔滨150001

出　　处：《运筹与管理》2008年第4期96-99,105,共5页Operations Research and Management Science

基　　金：国家自然科学基金资助项目(70773029);国家教育部博士点基金资助项目(20050213037);哈尔滨工业大学技术政策管理国家哲学社会科学创新基地资助;黑龙江省青年科学基金资助项目(QC04C25)

摘　　要：随着我国经济的快速发展,个人信贷业务扩大,给银行带来收益的同时必然存在风险,针对传统个人信用评估方法的不足,鉴于支持向量机具有全局收敛性和良好的推广能力,本文将这种方法应用到信用评估中,利用支持向量机的方法对个人信用进行实证评估,并与K最近邻模型方法进行比较,得出了该方法的可行性和优越性,为银行建立一套完善的评估体系提供依据。With the development of consumer credit in domestic commercial banks, personal credit is attached to more and more value in our country, which brings the bank both benefits and risks. In the light of dissatisfactions with existing personal credit scoring methods,the support-vector-machine （SVM） , which has many good properties including global convergence and good ability of extension, is put forward and applied to evaluate personal loan application. In this paper, the support vector machine （SVM） is applied to the study of personal credit risk assessment. In contrast with KNN, empirical results show that SVM is effective and more advantageous than other methods,which can help the bank establish a better assessment system.

关 键 词：管理科学 信用风险 支持向量机 个人信用评估 

分 类 号：N945.16[自然科学总论—系统科学]